Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add manu14357/zskills --skill azure-preparegit clone --depth 1 https://github.com/manu14357/zskillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/manu14357/zskills/azure-prepare)<a href="https://agentmods.dev/skills/manu14357/zskills/azure-prepare"><img src="https://agentmods.dev/badge/skills/manu14357/zskills/azure-prepare/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/manu14357/zskills/azure-prepare"><img src="https://agentmods.dev/badge/skills/manu14357/zskills/azure-prepare.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.02080 |
| Opus 5 | $0.00024 | $0.01040 |
| Sonnet 5 | $0.00010 | $0.00416 |
| Haiku 4.5 | $0.00005 | $0.00208 |
Grade A, and why
azure-prepare scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Prepare
Prepare subscriptions, resource groups, identity, governance, and cost controls per the Cloud Adoption Framework. Landing zone setup is foundational; all deployments depend on this layer.
Use This Skill When
- The user is starting a new Azure project or subscription
- Deployment keeps failing due to missing prerequisites (permissions, providers, quotas)
- The user asks for preflight checks, environment bootstrap, or landing zone design
- The user needs Azure Policy, tagging strategy, or access control baseline
Context: Landing Zone Maturity
Immature: Ad hoc resource creation, no policies, inconsistent naming, mixed environments
Developing: Basic resource groups, manual access control, some tagging
Managed: Landing zone deployed, policies enforced, RBAC standardized, centralized logging ← Target
Optimized: GitOps for infrastructure, automated drift detection, cost governance, full audit trail
Required Inputs
- Tenant and subscription: Tenant ID, subscription ID, billing account
- Environment scope: Single tenant or multi-tenant? Dev/test/prod separation?
- Region strategy: Primary and secondary regions, data residency constraints
- Naming convention: Org-env-workload-resource-seq (e.g.,
contoso-prod-web-vm-01) - Networking model: Hub-spoke, vWAN, or flat? Private or public endpoints?
- Identity model: Entra ID only, on-premises sync, hybrid?
- Security baseline: Encryption, firewalls, NSGs, private link requirements
- Team structure: Who owns the platform? Who owns workloads?
- Cost targets: Monthly budget, chargeback model, reserved capacity?
Decision Tree
Is this the first Azure subscription for the organization?
├─ Yes → Deploy landing zone from template (Microsoft Foundational or Enterprise)
└─ No → Align with existing landing zone patterns
Do you have on-premises infrastructure?
├─ Yes → Enable ExpressRoute, Site-to-Site VPN, DNS forwarders
└─ No → Direct internet egress acceptable
How many teams will share this subscription?
├─ Single team → Simple RBAC, one resource group per environment
└─ Multiple teams → Multiple resource groups, centralized policy, shared services
Are there compliance or regulatory requirements?
├─ Yes → Deploy Azure Policy, enable Defender, configure audit logging
└─ No → Basic security baseline sufficient
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 236 lines · 48 tokens per session scan A 12278fece7f8
azure-prepare is a skill published in the GitHub repository manu14357/zskills (16 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 2,080 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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